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Introduction
In high-pressure security operations centers, time is the most expensive resource. Analysts are often forced to make critical decisions with partial visibility, especially when endpoint data is missing and network telemetry becomes the primary source of truth. During Black Hat Europe, a simple but persistent analyst frustration sparked a practical innovation—one that transformed raw IP and domain data into actionable incident intelligence through automation, correlation, and XDR enrichment.
Summary of the Original
The story begins at the end of the first day of Black Hat Europe security operations. Over dinner near the Excel conference center, two NOC team members reflect on the day’s work. For René Straube, it is his first experience supporting the Black Hat Network Operations Center, and while the environment impresses him, a familiar pain point quickly surfaces.
René explains that during XDR investigations, analysts frequently encounter detections tied to public IP addresses without knowing why those connections occurred. Without EDR agents on endpoints, analysts lack visibility into the originating domain or URL. This gap slows investigations and adds uncertainty to incident response decisions. René initially assumes the data might be unavailable, but quickly realizes that the necessary information already exists within Splunk, sourced from Palo Alto Networks firewall DNS logs and Corelight OpenNDR connection logs.
Although Cisco and other partners were permitted to deploy pre-approved tools to improve visibility inside the Black Hat NOC, Cisco was not the official provider for XDR, SIEM, firewall, or NDR technologies. Despite this, the team identified an opportunity to automate enrichment workflows using existing telemetry.
The next morning, the idea becomes reality. Two automated workflows are built in under thirty minutes. The first maps domains to IP addresses by querying firewall DNS logs and, if necessary, Corelight network logs. The second performs the reverse—mapping IP addresses back to domains. Both workflows inject the resulting data directly into the XDR analytics platform, ensuring automatic correlation with active incidents.
These new actions are embedded into incident response playbooks, allowing analysts to trigger enrichment with minimal effort. The value of the automation becomes clear during a live incident triggered by Cisco Secure Access (Umbrella DNS), which flags malicious domains accessed from internal IP addresses on the Black Hat Europe Wi-Fi network.
Upon investigation, Cisco XDR confirms the malicious nature of the domains through threat intelligence enrichment. The analyst then uses the new playbook action to identify IP addresses associated with the suspicious domains. Within minutes, the incident is enriched with all related IPs observed in Palo Alto Networks and Corelight logs.
This enrichment reveals additional internal hosts communicating with the same infrastructure and uncovers URL patterns consistent with a phishing campaign. What could have taken hours is resolved in minutes, allowing the incident to be confidently escalated to a Level 3 analyst with sufficient context.
The article concludes by emphasizing the impact of listening to analyst feedback and using automation to eliminate repetitive investigative tasks. A small idea, born from frustration, delivers measurable operational value.
What Undercode Say:
This story highlights a reality many SOC teams quietly accept: the problem is rarely a lack of data, but a lack of usable context at the right moment. Network telemetry, DNS logs, and connection records are often siloed across platforms, forcing analysts to manually pivot between tools while attackers move faster.
What makes this case compelling is not the technology itself, but the mindset behind it. Instead of introducing yet another security product, the team leveraged what was already available—Splunk, firewall DNS logs, NDR data—and focused on automation that fits directly into analyst workflows. This is operational maturity in practice.
The bidirectional enrichment model—domains to IPs and IPs to domains—addresses a core investigative loop in network-centric incident response. Analysts think in pivots. When that pivot becomes a one-click action inside XDR, cognitive load drops and confidence increases.
Equally important is the decision to inject enrichment back into the XDR platform rather than leaving it as external context. Correlation is where raw data becomes intelligence. By ensuring enrichment events are part of the incident timeline, the team preserves investigative continuity and auditability.
This approach also demonstrates how XDR can remain valuable even without full EDR coverage. In environments like conferences, guest networks, or unmanaged devices, endpoint agents are unrealistic. Network-driven XDR enrichment fills that gap and keeps detection effective.
The rapid development time—thirty minutes—underscores another lesson: meaningful improvements do not always require long projects or architectural overhauls. Small, analyst-driven automations often deliver disproportionate returns.
Finally, the human element stands out. This innovation did not come from a roadmap or vendor pitch, but from a casual conversation and a willingness to listen. SOCs that cultivate this feedback loop consistently outperform those that rely solely on tooling.
Fact Checker Results
The workflow described relies on standard DNS and network connection logs commonly available in enterprise SOCs. ✅
The enrichment logic aligns with typical XDR correlation and playbook automation capabilities. ✅
The incident scenario reflects realistic SOC operations in large temporary networks such as security conferences. ✅
Prediction
XDR platforms will increasingly shift toward analyst-driven automation rather than vendor-defined workflows 🔮.
Network-based enrichment will become critical in environments where endpoint visibility is limited 🌐.
SOC teams that prioritize internal feedback loops will reduce incident resolution time more effectively than those adding new tools alone ⚡.
🕵️📝✔️Let’s dive deep and fact‑check.
References:
Reported By: blogs.cisco.com
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